SANNIX Thanksgiving Wine Glass Charms, 24Pcs Wine Charms for Stem Glasses Glass Identifier Charm for Thanksgiving Hostess Gift Tasting Party Gifts Favors

SANNIX Thanksgiving Wine Glass Charms, 24Pcs Wine Charms for Stem Glasses Glass Identifier Charm for Thanksgiving Hostess Gift Tasting Party Gifts Favors

ASIN: B0CF124MTV
Analysis Date: Nov 7, 2025 (re-analyzed Nov 7, 2025)

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Review Analysis Results

C
Authenticity Grade
28.00%
Fake Reviews
4.93
Original Rating
4.20
Adjusted Rating

Analysis Summary

The review set shows moderate authenticity concerns with several suspicious patterns. While many reviews appear genuine with specific usage scenarios (Galentines dinner, bachelorette party, Christmas party), there are notable red flags: 1) Extremely high 5-star rating concentration (14/15 reviews are 5-star, 93%), 2) Duplicate reviews from the same users (R36S51YC66DGES and R3YB8D9U0GU5C appear twice with identical text), 3) Some reviews use exaggerated marketing language ('Super Cute and EXQUISITE', 'posh and expensive') that mimics product descriptions, 4) Multiple reviews mention the same use cases (parties, gifts) with similar phrasing. However, the presence of one 4-star review, varied writing styles, and specific personal experiences provide some authenticity balance.

Review Statistics

442
Total Reviews on Amazon
-0.73
Rating Difference

Price Analysis

Price analysis pending

Price insights will be available shortly.

Understanding This Analysis

What does Grade C mean?

This product has moderate review authenticity concerns. A notable portion of reviews show suspicious patterns. Consider reading reviews carefully before purchasing.

Adjusted Rating Explained

The adjusted rating (4.20 stars) represents what we estimate this product's rating would be if fake reviews were removed. This product's adjusted rating is lower than Amazon's displayed rating (4.93 stars), suggesting positive fake reviews may be inflating the score.

How We Detect Fake Reviews

Our AI analyzes multiple factors: language patterns (generic vs. specific), reviewer behavior (history, timing), temporal anomalies (review clusters), verification status, sentiment authenticity, and statistical outliers. No single factor determines a review is fake - we look at the combination of signals.

Important Limitations

No automated system is perfect. Sophisticated fake reviews can evade detection, and some genuine reviews may be incorrectly flagged. Use this analysis as one data point in your purchasing decision, not the only factor. Reading actual review content yourself is always valuable.

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